Artificial Intelligence and Access to Childcare Support for Working Mothers in Lagos: Implications for Early Childhood Teacher Training and Workforce Development

Lemchi, Stella Ngozi *

Department of Home Economics and Hospitality Management Education, Alvan Ikoku Federal University of Education, Owerri, Imo State, Nigeria.

Mbah, Cynthia Adaku

Department of Home Economics and Hospitality Management Education, Alvan Ikoku Federal University of Education, Owerri, Imo State, Nigeria.

*Author to whom correspondence should be addressed.


Abstract

This study investigated the role of artificial intelligence (AI) in enhancing access to childcare support for working mothers in Lagos, Nigeria, and examined its implications for early childhood teacher training and workforce development. As urbanisation and women’s labour-force participation increase, the demand for affordable and flexible childcare solutions continues to exceed available provision in Lagos. AI-powered technologies, including automated childcare applications, virtual monitoring systems and intelligent scheduling platforms, are emerging as tools that may help address gaps in childcare support. The study assessed awareness, accessibility and utilization of AI-enabled child caretools among working mothersin Lagos, and examined how these tools relate to care practices and professional training needs in early childhood education. A mixed-methods research design was adopted. The study population comprised approximately two million working mothers in Lagos State, while a sample size of 400 respondents was determined using Taro Yamane’s sample-size formula. Data were collected from working mothers, early childhood educators and policy stakeholders through structured questionnaires, interviews and focus group discussions. Quantitative data were analysed using descriptive statistics, including mean and standard deviation, while SPSS version 27 was used to identify trends and relationships. Qualitative data were used to explore user experiences and policy perspectives. The findings showed that awareness of AI-enabled childcare tools was significantly higher than accessibility and utilisation. Although some mothers were aware of these tools, they reported barriers to access and consistent use. The study provides evidence-based insights for curriculum development in teacher education and for policy design aimed at the careful integration of AI technologies into childcare systems in Lagos and comparable urban settings.

Keywords: Artificial intelligence, childcare access, working mothers, Lagos, early childhood education, teacher training, workforce development, AI-enabled childcare tools, digital literacy, childcare policy.


How to Cite

Ngozi, Lemchi, Stella, and Mbah, Cynthia Adaku. 2026. “Artificial Intelligence and Access to Childcare Support for Working Mothers in Lagos: Implications for Early Childhood Teacher Training and Workforce Development”. Advances in Research 27 (4):307-17. https://doi.org/10.9734/air/2026/v27i41674.

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